Sistema fuzzy para estimativa do bem-estar de matrizes pesadas

Entender o comportamento e suas pequenas variações decorrentes das mudanças do ambiente térmico e desenvolver modelos que simulem o bem-estar a partir de respostas das aves ao ambiente constituem o primeiro passo para a criação de um sistema de monitoramento digital de aves em galpões de produção. Neste trabalho, foi desenvolvido um sistema de suporte à decisão com base na teoria dos conjuntos fuzzy para a estimativa do bem-estar de matrizes pesadas em função de frequências e duração dos comportamentos expressos pelas aves. O desenvolvimento do sistema passou por cinco etapas distintas: 1) organização dos dados experimentais; 2) apresentação dos vídeos em entrevista com especialista; 3) criação das funções de pertinência com base nas entrevistas e na revisão da literatura; 4) simulação de frequências de ocorrências e tempos médios de expressão dos comportamentos classificados como indicadores de bem-estar utilizando equações de regressão obtidas na literatura, e 5) construção das regras, simulação e validação do sistema. O sistema fuzzy desenvolvido estimou satisfatoriamente o bem-estar de matrizes pesadas, tendo na sua última versão, com maior número de regras, acertado 77,8% dos dados experimentais, comparados com as respostas esperadas por um especialista. O sistema pode ser utilizado como instrumento matemático-computacional para apoiar decisões em galpões de produção de matrizes pesadas.

Instituições de Ensino Superior e movimentos migratórios em Portugal: uma aplicação do método fuzzy

As Instituições de Ensino Superior (IES) localizam-se ao longo de todo o território português, em cidades de dimensão distinta mas sempre âncoras dos territórios envolventes. Um dos efeitos mais imediatos, entre os “efeitos de procura”, relaciona-se com a dimensão populacional das cidades onde as IES estão instaladas. Logo que todos os agentes diretamente envolvidos com a IES chegam à (permanecem na) cidade – funcionários docentes e não docentes e estudantes – provocam efeitos vários, quer pela dimensão demográfica (quer em termos de volume quer de estrutura) quer pelos efeitos multiplicadores na atividade económica. O enquadramento teórico deste estudo prende-se com duas teorias fundamentais: os estudos acerca dos impactes das IES e a teoria das migrações jovens. Esta investigação visa estudar a existência de correlações entre as cidades que acolhem as IES, estas instituições e os movimentos migratórios ao longo do país. As questões de investigação são as seguintes: a dimensão das IES está relacionada com a dimensão da cidade onde está instalada e a capacidade de atração de ambas é proporcional? Podem as IES servir para inverter os fluxos migratórios que se verificam com destino às cidades onde existem IES? Os objectivos do trabalho são: - relacionar a dimensão das IES com as cidades de acolhimento, bem como os respectivos níveis de atração; - estudar os fluxos migratórios, destacando os jovens do conjunto do total da população que se desloca para as cidades / concelhos onde existem IES. Utilizar-se-ão dados relativos i) aos estabelecimentos da rede pública, universitária e politécnica; ii) às migrações internas em Portugal por grupos de idades e, iii) caracterização das cidades de acolhimento das IES. Os dados serão analisados com métodos de estatística descritiva, multivariada e com a metodologia fuzzy que visa conhecer as condições necessárias e/ou suficientes da atratividade das cidades relativamente aos fluxos migratórios jovens.

Tourism Destination Preferences: A Longitudinal Analysis of Consumer Decision Sets

There have only been a small number of applications of consumer decision set theory to holiday destination choice, and these studies have tended to rely on a single cross sectional snapshot of research participants’ stated preferences. Very little has been reported on the relationship between stated destination preferences and actual travel, or changes in decision set composition over time. The paper presents a rare longitudinal examination of destination decision sets, in the context of short break holidays by car in Queensland, Australia. Two questionnaires were administered, three months apart. The first identified destination preferences while the second examined actual travel and revisited destination preferences. In relation to the conference theme, there was very little change in consumer preferences towards the competitive set of destinations over the three month period. A key implication for the destination of interest, which, in an attempt to change market perceptions, launched a new brand campaign during the period of the project, is that a long term investment in a consistent brand message will be required to change market perceptions. The results go some way to support the proposition that the positioning of a destination into a consumer’s decision set represents a source of competitive advantage.

Applying data mining to assess crash risk on curves

The wide range of contributing factors and circumstances surrounding crashes on road curves suggest that no single intervention can prevent these crashes. This paper presents a novel methodology, based on data mining techniques, to identify contributing factors and the relationship between them. It identifies contributing factors that influence the risk of a crash. Incident records, described using free text, from a large insurance company were analysed with rough set theory. Rough set theory was used to discover dependencies among data, and reasons using the vague, uncertain and imprecise information that characterised the insurance dataset. The results show that male drivers, who are between 50 and 59 years old, driving during evening peak hours are involved with a collision, had a lowest crash risk. Drivers between 25 and 29 years old, driving from around midnight to 6 am and in a new car has the highest risk. The analysis of the most significant contributing factors on curves suggests that drivers with driving experience of 25 to 42 years, who are driving a new vehicle have the highest crash cost risk, characterised by the vehicle running off the road and hitting a tree. This research complements existing statistically based tools approach to analyse road crashes. Our data mining approach is supported with proven theory and will allow road safety practitioners to effectively understand the dependencies between contributing factors and the crash type with the view to designing tailored countermeasures.

A role mining inspired approach to representing user behaviour in ERP systems

Despite all attempts to prevent fraud, it continues to be a major threat to industry and government. Traditionally, organizations have focused on fraud prevention rather than detection, to combat fraud. In this paper we present a role mining inspired approach to represent user behaviour in Enterprise Resource Planning (ERP) systems, primarily aimed at detecting opportunities to commit fraud or potentially suspicious activities. We have adapted an approach which uses set theory to create transaction profiles based on analysis of user activity records. Based on these transaction profiles, we propose a set of (1) anomaly types to detect potentially suspicious user behaviour and (2) scenarios to identify inadequate segregation of duties in an ERP environment. In addition, we present two algorithms to construct a directed acyclic graph to represent relationships between transaction profiles. Experiments were conducted using a real dataset obtained from a teaching environment and a demonstration dataset, both using SAP R/3, presently the most predominant ERP system. The results of this empirical research demonstrate the effectiveness of the proposed approach.

Transaction mining for fraud detection in ERP Systems

Despite all attempts to prevent fraud, it continues to be a major threat to industry and government. Traditionally, organizations have focused on fraud prevention rather than detection, to combat fraud. In this paper we present a role mining inspired approach to represent user behaviour in Enterprise Resource Planning (ERP) systems, primarily aimed at detecting opportunities to commit fraud or potentially suspicious activities. We have adapted an approach which uses set theory to create transaction profiles based on analysis of user activity records. Based on these transaction profiles, we propose a set of (1) anomaly types to detect potentially suspicious user behaviour, and (2) scenarios to identify inadequate segregation of duties in an ERP environment. In addition, we present two algorithms to construct a directed acyclic graph to represent relationships between transaction profiles. Experiments were conducted using a real dataset obtained from a teaching environment and a demonstration dataset, both using SAP R/3, presently the predominant ERP system. The results of this empirical research demonstrate the effectiveness of the proposed approach.

A Two-stage information filtering based on rough decision rule and pattern mining

Information Overload and Mismatch are two fundamental problems affecting the effectiveness of information filtering systems. Even though both term-based and patternbased approaches have been proposed to address the problems of overload and mismatch, neither of these approaches alone can provide a satisfactory solution to address these problems. This paper presents a novel two-stage information filtering model which combines the merits of term-based and pattern-based approaches to effectively filter sheer volume of information. In particular, the first filtering stage is supported by a novel rough analysis model which efficiently removes a large number of irrelevant documents, thereby addressing the overload problem. The second filtering stage is empowered by a semantically rich pattern taxonomy mining model which effectively fetches incoming documents according to the specific information needs of a user, thereby addressing the mismatch problem. The experimental results based on the RCV1 corpus show that the proposed twostage filtering model significantly outperforms the both termbased and pattern-based information filtering models.

aa-cell in practice : an approach to musical live coding

Live coding performances provide a context with particular demands and limitations for music making. In this paper we discuss how as the live coding duo aa-cell we have responded to these challenges, and what this experience has revealed about the computational representation of music and approaches to interactive computer music performance. In particular we have identified several effective and efficient processes that underpin our practice including probability, linearity, periodicity, set theory, and recursion and describe how these are applied and combined to build sophisticated musical structures. In addition, we outline aspects of our performance practice that respond to the improvisational, collaborative and communicative requirements of musical live coding.

RCA method for fault diagnosis in digital substations of power systems

The authors present a Cause-Effect fault diagnosis model, which utilises the Root Cause Analysis approach and takes into account the technical features of a digital substation. The Dempster/Shafer evidence theory is used to integrate different types of fault information in the diagnosis model so as to implement a hierarchical, systematic and comprehensive diagnosis based on the logic relationship between the parent and child nodes such as transformer/circuit-breaker/transmission-line, and between the root and child causes. A real fault scenario is investigated in the case study to demonstrate the developed approach in diagnosing malfunction of protective relays and/or circuit breakers, miss or false alarms, and other commonly encountered faults at a modern digital substation.

Destination branding performance measurement : a non-technical discussion for practitioners

While academic interest in destination branding has been gathering momentum since the field commenced in the late 1990s, one important gap in this literature that has received relatively little attention to date is the measurement of destination brand performance. This paper sets out one method for assessing the performance of a destination brand over time. The intent is to present an approach that will appeal to marketing practitioners, and which is also conceptually sound. The method is underpinned by Decision Set Theory and the concept of Consumer-Based Brand Equity (CBBE), while the key variables mirror the branding objectives used by many destination marketing organisations (DMO). The approach is demonstrated in this paper to measure brand performance for Australia in the New Zealand market. It is suggested the findings provide indicators of both i) the success of previous marketing communications, and ii) future performance, which can be easily communicated to a DMO’s stakeholders.

Destination branding performance measurement for practitioners

While academic interest in destination branding has been gathering momentum since the field commenced in the late 1990s, one important gap in this literature that has received relatively little attention to date is the measurement of destination brand performance. This paper sets out one method for assessing the performance of a destination brand over time. The intent is to present an approach that will appeal to marketing practitioners, and which is also conceptually sound. The method is underpinned by Decision Set Theory and the concept of Consumer-Based Brand Equity (CBBE), while the key variables mirror the branding objectives used by many destination marketing organisations (DMO). The approach is demonstrated in this paper to measure brand performance for Australia in the New Zealand market. It is suggested the findings provide indicators of both i) the success of previous marketing communications, and ii) future performance, which can be easily communicated to a DMO’s stakeholders.

Feature selection using expected attainable discrimination

We propose expected attainable discrimination (EAD) as a measure to select discrete valued features for reliable discrimination between two classes of data. EAD is an average of the area under the ROC curves obtained when a simple histogram probability density model is trained and tested on many random partitions of a data set. EAD can be incorporated into various stepwise search methods to determine promising subsets of features, particularly when misclassification costs are difficult or impossible to specify. Experimental application to the problem of risk prediction in pregnancy is described.

Principles of Pitch Organization in Béla Bartók's 'Duke Bluebeard's Castle'

The topic of my doctoral thesis is to demonstrate the usefulness of incorporating tonal and modal elements into a pitch-web square analysis of Béla Bartók's (1881-1945) opera, 'A kékszakállú herceg vára' ('Duke Bluebeard's Castle'). My specific goal is to demonstrate that different musical materials, which exist as foreground melodies or long-term key progressions, are unified by the unordered pitch set {0,1,4}, which becomes prominent in different sections of Bartók's opera. In Bluebeard's Castle, the set {0,1,4} is also found as a subset of several tetrachords: {0,1,4,7}, {0,1,4,8}, and {0,3,4,7}. My claim is that {0,1,4} serves to link music materials between themes, between sections, and also between scenes. This study develops an analytical method, drawn from various theoretical perspectives, for conceiving superposed diatonic spaces within a hybrid pitch-space comprised of diatonic and chromatic features. The integrity of diatonic melodic lines is retained, which allows for a non-reductive understanding of diatonic superposition, without appealing to pitch centers or specifying complete diatonic collections. Through combining various theoretical insights of the Hungarian scholar Ernő Lendvai, and the American theorists Elliott Antokoletz, Paul Wilson and Allen Forte, as well as the composer himself, this study gives a detailed analysis of the opera's pitch material in a way that combines, complements, and expands upon the studies of those scholars. The analyzed pitch sets are represented on Aarre Joutsenvirta's note-web square, which adds a new aspect to the field of Bartók analysis. Keywords: Bartók, Duke Bluebeard's Castle (Op. 11), Ernő Lendvai, axis system, Elliott Antokoletz, intervallic cycles, intervallic cells, Allen Forte, set theory, interval classes, interval vectors, Aarre Joutsenvirta, pitch-web square, pitch-web analysis.

On linear order and computation : The expressiveness of interactive computations on linear orders and computations indexed by ordinals

We solve the Dynamic Ehrenfeucht-Fra\"iss\'e Game on linear orders for both players, yielding a normal form for quantifier-rank equivalence classes of linear orders in first-order logic, infinitary logic, and generalized-infinitary logics with linearly ordered clocks. We show that Scott Sentences can be manipulated quickly, classified into local information, and consistency can be decided effectively in the length of the Scott Sentence. We describe a finite set of linked automata moving continuously on a linear order. Running them on ordinals, we compute the ordinal truth predicate and compute truth in the constructible universe of set-theory. Among the corollaries are a study of semi-models as efficient database of both model-theoretic and formulaic information, and a new proof of the atomicity of the Boolean algebra of sentences consistent with the theory of linear order -- i.e., that the finitely axiomatized theories of linear order are dense.